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By Douglas Banks

Construction for the new 2.5 MGPD raw water intake project commenced December 2002. The project, initially designed as a 12' Ø concrete lined intake shaft,145' deep, with two offset 24" lake taps, 520' and 470' long was subsequently “value engineered” running the two lake taps through a single conduit. The offset for summer and winter pools was accomplished via a second shaft located at the lakes edge. Construction involved the use of blind drilling techniques for the shaft development and drill and blast techniques for the tunneling. All works were completed through extremely hard crystallized sandstone. The project came online August 12, 2004.

Jan 1, 2005

By J. Restrepo, N. Ripepi

"The International Organization of Standards defines risk as “the effect of uncertainties on achieving objectives (15).” In mining, many uncertainties can influence the outcome of personal or professional objectives and are often difficult to predict. Risk management, the minimization and control of adverse effects from exposure to identified risks, is a well-established concept that can summarized as “being smart about taking chances” (12). Risk management now consists of management processes unique to numerous organizations across many industries, as varying sectors encounter a variety of needs, including the analysis and mitigation of risks related to physical security, product liability, information security, various forms of insurance, regulatory compliance, and workplace safety (12). The reoccurrence of multiple fatality events in the US mining industry, especially the underground coal sector, suggests an opportunity for improved methods of major safety hazard identification, assessment, and mitigation. A risk management approach would include ready identification and mitigation of these risks, inclusive stakeholder engagement, and rapid integration. While many solutions to reducing the risk of mine disasters have been proposed including stricter regulation and improved technology, a comprehensive risk management approach has yet to be fully integrated in the US mining industry. In December of 2006, R. Larry Grayson of the National Mining Association’s Mine Safety Technology and Training Commission called for “a new paradigm for ensuring safety in underground coal mines, one that focuses on systematic and comprehensive risk management as the foundation from which all life-safety efforts emanate (7).” A risk management approach has already been implemented with success in Australia’s minerals industry as part of a transition during the mid-1990s from a prescriptive based health and safety attitude to a more proactive, duty-of care [risk-based] philosophy (13, 16, 17).FUNDAMENTAL ELEMENTS OF RISK MANAGEMENT TECHNIQUES The fundamental components of a comprehensive risk assessment/management program are well-established within the realm of mining health and safety. Figure 1 depicts the elements of a typical mining hazard management framework. The first step in any safety-based risk management system is to identify and assess hazards by their location, nature, and magnitude within a mine. Next, a decision is made about choosing to eliminate, mitigate, or tolerate each hazard. Ideally, a hazard will be eliminated during the design stages of mining, though dynamic mining conditions often require continuous improvement and reevaluation of existing hazard controls. If elimination is not possible, hazard mitigation actions can consist of methods, rules, equipment, competencies, or other mechanisms. If a hazard is simply tolerated, as many inherent mining hazards must be, then specialized administrative controls must be utilized to minimize losses. During this process, the performance of each action is monitored and modified as needed (13)."

Jan 1, 2015

By Nikhil Dhawan, Shrey Agrawal

India’s most extensive renewable energy expansion program targets 280 GW of solar energy by 2030. Due to the massive generation of photovoltaic waste (expected 34,600 T by 2030), stringent recycling effort to recover metal resources from endof- life PVs is required for resource recovery, circular economy, and subsequent reduction in the environmental impact. The present study investigates the recycling potential of end-of-life silicon solar modules. The feed characterization reveals that most of the values in PV modules are concentrated in the frame (pure Al), Si wafer (72–84% Si, 9–12% Al, and 0.13–0.71% Ag), and electrical connections (Cu wire coated with Sn). The Si and Ag values in the feed were beneficiated using water fluidization, and concentrate with 90% Si and 2% Ag was attained in the underflow concentrate. Ag values were recovered in the form of AgCl by leaching in nitric acid and precipitation. After the purification step, the residue containing 99% Si can be further utilized to fabricate Si wafer and Al-Si alloy. The preliminary cost estimations suggest that the proposed process is economically viable for the recycling of solar panels with the maximum value generated from the AgCl precipitate followed by Al panels and Si wafers.

Nov 14, 2022

By M. Spangler

FirstMiss Gold installed a supervisory control system based on Pavilion Technology's Process Insights neural network software and Oil System's PI data historian. The primary goal of the system was to control the acid preconditioning circuit. However, our first successful control loop was on the limestone feed rate to the neutralization circuit. The information gained by modeling these circuits and the better control provided by the system has resulted in reagent savings of over $80,000 per month.

Jan 1, 1995

By M. R. Wormald

A real time data acquisition system has been developed for implementing standard radiometric analytical techniques, applied to the monitoring and control of mineral processing plants. The system uses standard ECB-bus microprocessors and peripherals, in conjunction with a specially designed nucleonic pulse ADC. It is being applied to the accurate on-line analysis of naturally-,occurring radioelements in processing plants, for example by simultaneously measuring the intensity of 1.46 MeV gamma-rays from the naturally-occurring radioisotope K-40, and the stream density by gamma-ray transmission of 662 keV gamma-rays. Gain stabilisation of the NaI(T1) scintillation detectors is maintained by the microprocessor in slave units, each of which may control up to four sample presentation systems. Data analysis - including corrections for bulk density, radioactive decay of the Cs-137 gamma-ray source, pulse pile-up, dead time and external background - is carried out in a master computer which is connected to the slave unit, and can be interfaced to the plant control computer via data links.

Jan 1, 1986

By Chiranjibi Santi, Amit Kumar Gorai, VIVEK KUMAR HIMANSHU

Air overpressure (AOp) and peak particle velocity (PPV) are the most undesirable effects of blasting in mines. It is an urgent need to design a predictor model for AOp and PPV for universal applications to minimize environmental effects and damages that occur due to blasting. The present study attempts to design an artificial neural network (ANN) model for the prediction of AOp and PPV in different conditions. In this study, the blast design parameters (number of holes, depth of the blast hole, stemming length, spacing, burden, distance of vibration monitoring location from the blast site, charge weight per delay) of two active mines (coal and iron ore) are considered in four different conditions for training and testing of the model for the prediction of AOp and PPV. The model was trained and tested in four different combinations of data (trained using data of one mine and tested using data of another mine, trained and tested using data of coal mine, trained and tested using data of an iron ore mine, trained and tested using combined data of both the mines) for examining the applicability in different conditions. The results indicate that R2 values are ranged from 0.886 to 0.908 and 0.8728 to 0.8959, respectively, in the prediction of PPV and AOp. A comparative study of the performances of the developed model with the other empirical model is also demonstrated. For this, the site constants of different empirical models were estimated individually for both the mines. The study results indicated that the ANN model performs much better than all the empirical models. It can be inferred from the results that blast vibration cannot be accurately predicted only from charge per delay and distance from the blast hole. The ANN model was considered many other factors and thus can predict the vibration level more accurately.

Jul 30, 2021

By T. Rasmussen, T. G. Jørgensen, T. Fischer, R. K. McLimans, C. Knudsen, D. Frei

Ilmenite-bearing paleo-beach deposits were discovered in Jylland, Denmark using a combination of Ground Penetrating Radar (GPR), portable X-ray fluorescence (XMET), bulk XRF analyses, Computer Controlled Scanning Electron Microscopy (CCSEM), and wire line logging. The Miocene-age paleo-beach deposits are located below a thin Quaternary cover in a region of very moderate relief and essentially no outcrop demanding unique approaches in exploration. Initially, an isopach map of the Quaternary is prepared from existing water well data. A geological model for likely occurrence of Miocene paleo-beach deposits is generated and the coincidence of thin Quaternary cover and potential paleo-beach deposits define targets for detailed exploration. The defined targets are traversed with GPR to identify paleo-beach structures which are then used to define a drilling program. This methodology located a paleo-barrier island at the Vorslunde location with more than 10% ilmenite in the sand. During the drilling process, the TiO2 and heavy mineral contents of the sand were logged every meter with a portable XRF unit (XMET) and subsequently calibrated more accurately by comparison to bulk XRF and CCSEM analyses for selected samples. The bulk XRF data also provided more complete compositional information. Insitu determination of geology, heavy mineral abundance, and corroboration of the XRF logging was done using wire line logs, a combination of spectral gamma and induction conductivity logs. Detailed characteristics (abundance, grain size, shape) and chemical composition of minerals was determined by the GEUS CCSEM methodology (Frei et al, this vol.). The average weight percent TiO2 for all Ti-minerals is 62%, 60% excluding rutile. That elevated TiO2 content (>> ilmenite stoichiometric value, ca. 50 %) indicates that ilmenite experienced an iron-leaching environment. The source of the sand deposit was investigated by dating contained zircon. The results show that the likely sources of zircon are in southern Norway and southwestern Sweden with common zircon ages of ca 1100 Ma. and 1500 Ma.

Jan 1, 2005

By Dejan Petrović, Pavle Stojković, Jelena Ivaz, Saša Stojadinović

In spite of the fact that flyrock phenomenon represents the real threat for personnel and machinery, it still remains insufficiently investigated. There are efforts, in the mining community, to explain the causes of flyrock, but the models capable to accurately predict flyrock occurrence and define the flyrock distance still do not exist. This article is an attempt to establish such a predictive model. The model utilized the adaptive nature of artificial neural networks and combined it with the accuracy of numerical modeling of physical phenomena. Necessary data were collected by high-speed camera recordings of actual blasts at three different surface mines and processed for further use for artificial network training. The result was a neuro-numerical couple which was capable to predict flyrock occurrence, estimate the launch velocity of flyrock fragments, and calculate the maximum distance of flyrock fragments. The safe distance was then calculated by multiplying the flyrock distance with a factor of safety. The article explains the procedure for data acquisition and processing, artificial network construction, training, and validation. It also explains the principles of flyrock distance calculation and, finally, provides a definition of factor of safety and safe distance. The results showed that the prediction was satisfactorily accurate and reliable.

Oct 22, 2021

By Ray Wood, Rene Sterk, Robin Falconer, Sean Aldrich, Simon Nielsen

"The Chatham Rock Phosphorite project is situated 450 km east of New Zealand at approximately 350 to 450 m water depth. The deposit occurs as a thin layer of phosphatebearing glauconitic sand at the surface of the sea floor and has a thicknesses typically ranging from 0 to 1 m. The sand layer consists of mainly silt and sand-sized sediments, with phosphatised chalk nodules up to 15 cm in diameter. Phosphate nodules were first discovered on the Chatham Rise in the 1950s by a New Zealand Government survey. During the 1960s to 1980s several private and government sponsored cruises explored the Chatham Rise and surrounding seafloor area. A total of 1174 samples were collected over a 600 km2 area with the majority of the samples collected using a pneumatic -or large Van Veen-style grab-sampler.Since acquiring the licence in 2010, Chatham Rock Phosphate Limited has conducted six cruises in two programs in the Project area. A total of 261 samples were collected using a Van Veen grab, box core and grab samples.Sample quality and QA/QC measures varied considerably between the cruises and within each cruise. A critical part of the assessment of the data collected in the Project area was to determine what quality thresholds to use to allow or disallow data to enter into the estimation process. As part of the data verification process, the relative and absolute quality of the data was assessed in as much detail as practically possible. The best samples were those that were collected using the pneumatic grab, sampled the full sand horizon, had a small location survey error and had no other apparent data ambiguities. This paper describes the challenges for mineral resource estimation for an unconventional style of mineralisation using unconventional sampling techniques."

Sep 1, 2014

By D. Parks, A. Miller, M. McNinch, R. Jacksha

Each year, hundreds of mine workers are involved in machinery-related accidents. Many of these accidents involve inadequate or improper use of lockout/tagout (LOTO) procedures. To mitigate the occurrence of these accidents, new safety methods are needed to monitor access to hazardous areas around operating machinery, improve documentation/monitoring of maintenance that requires shutdown of the machinery, and prevent unexpected startup or movement during machine maintenance activities. The National Institute for Occupational Safety and Health (NIOSH) is currently researching the application of Internet of Things (IoT) technologies to provide intelligent machine monitoring as part of a comprehensive LOTO program. This paper introduces NIOSH’s two phase implementation of an IoT-based intelligent machine monitoring system. Phase one is the installation of a proof-of-concept system at a concrete batch plant, while phase two involves scaling up the system to include additional sensors, more detailed safety/performance metrics, proximity detection, and predictive failure analysis.

By I. M. Ahmed, R. S. Hassan, M. I. Aly

Extraction and separation of La, Sm and Dy ions from acidic sulfate-phosphate solutions was investigated using a cation exchange extractant, bis(2,4,4-trimethylpentyl) phosphinic acid, CYANEX 272, in kerosene. The influence of shaking time, equilibrium pH, extractant, sulfate and phosphate ion concentrations, diluent type and temperature was studied. The extraction was found to be pH-dependent, and increasing the phosphate ion concentration inhibited the extraction which was found to be endothermic. The stoichiometry of the extracted metal species was found to be MOH.H2OHSO4H2A.A2. Aliphatic diluents were found to enhance the extraction compared to aromatic diluents. The results showed that there was a separation mode between the metal ions when varying the hydrogen ion and sulfate ion concentrations, under the used experimental conditions. The investigated process was used for the recovery of La, Sm and Dy from the acid solution resulting from the leaching of low-grade monazite.

By Y. C. Kim

This paper describes the implementation aspect of a blast hole kriging system which has been developed for the purpose of daily ore-waste control in an open pit mine. The primary goal of blast hole kriging is to improve the ore-waste delineation procedure. A complete computer program package called Blast Hole Kriging (BHK) System was developed for IBM/PC AT or XT computer, using Fortran language and supplemented by a few Assembly language routines for bit-map manipulation. The emphasis of this paper is on the implementation aspect of the developed system. For this reason, the requirements for practical implementation and the system design considerations are discussed in the paper, as well as the main features of the University of Arizona's BHK System.

Jan 1, 1990

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

Sep 3, 2019

By W. F. Visser

The growing availability of information and data analysis capabilities of recent years provides new opportunities for improving the performance of mining operations. By using real-time measurements and artificial intelligence, it is possible to respond faster to changing conditions, while accurate and timely information permits rapid evaluation of changes and fast business improvement decisions. This article presents a blueprint for alignment of systems, organizational design, and management practices to leverage these developments in performance-driven operations management in mining and mineral processing. The first component of the blueprint is a performance framework with a system of key performance indicators for production control that can be used across organizational levels. This system places improvement at the core of management activities, giving greater importance to improvement skills at lower organizational levels, so companies can leverage available information for improving operational control. Secondly, the blueprint defines an organizational structure that strengthens performance improvement with technological and change management capabilities. Finally, the blueprint proposes alignment of management practices, covering the optimization of short-interval controls, the application of an improvement project portfolio management system that determines the ownership of improvement projects, and the coordination of controls across the organization. This combination of systems, organizational design, and management alignment supports rapid decision-making at the right organizational level. Introduction of the presented blueprint for operations management enables mines to leverage the developments in information and analysis capabilities to improve the performance of operations.

By Cem Şensöğüt, Özer Ören, Yaşar Kasap

The mining sector, which has an important place in terms of raw material and energy supply, is referred as a sector with one of the highest fatal accidents in comparison with other sectors. In this century, where occupational health and safety awareness has increased, it is important to review the past accident statistics and to determine the current deficiencies by using the information in the inventory. In this study, the Malmquist total factor productivity index (MPI) has been utilized to investigate the changes in the work accidents occurring in the Western Lignite Corporation (Turkey), where underground and surface production methods are applied, and to determine the measures to be taken. According to the results obtained, both the decrease in production amount and the increase in the number of accidents caused inefficiencies during the period in concern due to the expected 10-year economic life of the mechanized system operating in the underground production panel that came to an end in 2007 and the flooding took place in early 2017. Compared with the underground operations, it has been determined that production can be carried out at the appropriate scale despite the heavy working conditions encountered due to the changing climatic conditions and the progress of production in the surface operations.

By Jacob Carr, Bruce Whisner, Adam Smith, Jingcheng Li

Electromagnetic-based proximity detection systems (PDSs) are utilized on mining machinery to protect workers from being pinned or struck. These systems generate magnetic fields covering the space around a machine, and a miner-wearable component (MWC) detects the field. The PDS determines the distance of miners relative to the machine based on the detected magnetic flux density in the magnetic field. This information is used to establish warning and shutdown zones around the machine. Maintaining a stable magnetic field is essential for system accuracy. However, components used to generate magnetic fields can be influenced by temperature changes. Depending on ventilation conditions and seasonal alternation, a PDS can be subject to significant temperature fluctuation. To better understand and quantify this phenomenon, researchers from the National Institute for Occupational Safety and Health (NIOSH) developed an experimental apparatus to study the influence of temperature on magnetic field generator circuits used in PDSs. Results from the study show that the electric current through a generator can be influenced by both ambient and internal temperatures, modifying the magnetic field that is produced. These findings show that temperature can significantly influence the ability of PDSs, used in underground coal mines, to accurately determine a worker’s position in relation to mining machine.

By G. M. Rao, P. N. Deo

Graphite is soft and easily floatable but it is quite difficult to obtain high purity concentrate at coarse sizes. Chemical treatment can produce high grade concentrate but it is an expensive process. Graphite containing plus 96% fixed carbon (FC) with coarse flakes commands high price in international market. Such graphite concentrate containing plus 96% FC was produced in Indian Bureau of Mines (IBM) by using newly developed reagent (mixture of different hydrocarbons and terpenes, IBM/D7) instead of commonly used frothers viz. pine oil, MIBC, kerosine etc. and regrinding in a special type of mill with special grinding media instead of grinding in a conventional ball/ rod mill followed by cleaning. Both the new reagent (frother) and special grinding media are inexpensive and readily available. The process is under patenting. This paper focuses application of this new grinding methodology for flake size protection, and the new reagent for selective flotation of high purity graphite.

Jan 1, 1995

From the massive equipment that moves the earth, to the parts that keep the equipment moving, it was all on display for more than 35,000 people who at-tended MinExpo 2008 at the Las Vegas Convention Center Sept. 22-24. In the largest show in the illustrious history of MinExpo, the success of the recent commodity boom was reflected in the more than 55,700 hm2 (600,000 sq ft) of floor space that was jam-packed with nearly 1,300 vendors. Among them, the makers of the industry?s largest machines, displaying their latest and greatest trucks, shovels, excavators, drills and other mining equipment. During the nearly decade-long commodities boom, equipment makers have worked hard to keep up with demand while also investing heavily in research and development. The beneficiaries of this R&D is the end user who saw first-hand at MinExpo 2008 the many advances that have already been made in safety, comfort and productivity from all the manufacturers. R&D has also helped spark more talk of automation, which is being used already at some of the world?s largest mines. Caterpillar and Komatsu have worked with the technology in surface mining and Bucyrus and Sandvik are among the industry leaders applying the science of automation to underground mines. Technology has in-creased greatly since the idea of moving massive equipment remotely was first knocked around and the idea of entire fleets operating around the clock seems to be getting closer to reality. But, until that happens, MinExpo attendees were treated to a show that featured some of the most impressive current machines the industry has to offer. In the largest booth space of the convention, Caterpillar (www.cat.com) displayed the culmination of an ambitious $280-million dollar investment, with the introduction of its new mining fleet of four new trucks. The F-series was un-veiled with common features in safety, cabs, engines, frames and bodies and Tier 2 compliant engines. The F series also features a return to the electric drive option. ?When our customers asked us for improvements to our mining trucks, we responded by making a record investment in every single truck in our line, as well as the increased capacity to produce more of them,? said Cater-pillar group president Stu Levenick. ?New technologies have allowed us to make trucks more reliable, easier to maintain and more friendly to the operator and to the environment.? The 793-series is in the 218- to 227-t (240- to 250-st) class that will be available in both mechanical (793F) and electric (793F ac) versions. The electric drive-only 313- t (345-st) 795F was also introduced, while the flagship 797B truck is in the process of being replaced by the new 797F mechanical drive, maintaining its 345- to 363-t (380- to 400-st) target payload. Completing Caterpillar?s new mining truck line will be new versions of the 785 and 789 mechanical drive trucks. The next generation of trucks will be phased into production during the next two years, with the Cat ac drive models expected to go into production in late 2010. The $280-million in-vestment is Caterpillar?s largest commitment ever to the mining industry

Jan 1, 2008